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SURVIVAL AND EXTINCTION IN THE REPLICATOR MODEL: DYNAMICS AND STATISTICS [PDF]
Advances in Complex Systems, 2003 We study the multi-species replicator model with linear fitness and random fitness matrices of various classes. By means of numerical resolution of the replicator equations, we determine the survival probability of a species in terms of its average interaction with the rest of the system.
SEBASTIÁN BOUZAT, DAMIÁN H. ZANETTE
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Statistical Assessment of Biomarker Replicability using MAJAR Method
Statistical Methods in Medical Research, 2022Abstract In the era of precision medicine, many biomarkers have been discovered to be associated with drug efficacy and safety responses, which can be used for patient stratification and drug response prediction. Due to small sample size and limited power of randomized clinical studies, meta-analysis is usually conducted to aggregate ...
Yuhan Xie +5 more
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Statistical Significance and Replicability
Theory & Psychology, 1998Commentators agree with me that statistical significance does not betoken replicability, but not for the reasons I give. Chow (1998) defends the use of significance tests by arguing that they are useful for assessing the role of chance in findings. I dispute this by pointing out that the Type II error rate may be as high as 1 - ct.
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Reconsidering statistical methods for assessing replication.
Psychological Methods, 2021Recent empirical evaluations of replication in psychology have reported startlingly few successful replication attempts. At the same time, these programs have noted that the proper way to analyze replication studies is far from a settled matter and have analyzed their data in several different ways.
J. M. Schauer, L. V. Hedges
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Statistical Comparison of Original and Replicated Surfaces
2019This article is focused on the statistical comparison of the original and replicated surface. Surface replication has been used for a long time, but recently a material with the commercial name Dentacryl™ has been used for the replication. However, this material has some disadvantages that outweigh the benefits.
Kubišová, Milena +3 more
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Statistical Methods for Replicability Assessment
2022The reproducibility of scientific discoveries is a hallmark of scientific research. Although its centrality is widely appreciated in the scientific community, precise definitions for reproducibility and quantitative approaches for replicability assessment are still lacking.
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Mutation–Replication Statistics of Polymerase Chain Reactions
Journal of Computational Biology, 2002The variability of the products of polymerase chain reactions, due to mutations and to incomplete replications, can have important clinical consequences. Sun (1995) and Weiss and von Haeseler (1995) modeled these errors by a branching process and introduced estimators of the mutation rate and of the efficiency of the reaction based, for example, on the
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Statistical Methods for Analyzing Microarray Feature Data with Replications
Journal of Computational Biology, 2003Expression levels in oligonucleotide microarray experiments depend on a potentially large number of factors, for example, treatment conditions, different probes, different arrays, and so on. To dissect the effects of these factors on expression levels, fixed-effects ANOVA methods have previously been proposed.
Yaning Yang +6 more
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Replicated measurements and algebraic statistics
2009A basic application of algebraic statistics to design and analysis of experiments considers a design as a zero-dimensional variety and identifies it with the ideal of the variety. Then, a subset of a standard basis of the design ideal is used as support for identifiable regression models. Estimation of the model parameter is performed by standard least
NOTARI, ROBERTO, E. Riccomagno
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A Useful Statistical Technique for Replication Studies
Journal for Research in Mathematics Education, 1977Eastman's (1975) recent expression in the JRME of concern over so few replication studies is a concern that should be shared by all who have an interest in research. Replication is critical in assessing the "significance" of research results. A correlation coefficient of .20, which is statistically significant at the .01 level, will be much more ...
Randy Ellsworth, Richard L. Isakson
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